AI Agencies: From Development to Education & Consulting

The AI Agency Shift: From Development to Education and Consulting

The landscape of AI agencies is evolving beyond pure software development. A significant entry point, particularly for non-technical professionals, lies in providing education, consulting, and staff training. This deep dive explores how a non-technical individual, Matteo, generated substantial revenue by focusing on AI training and education as a “foot-in-the-door” offer, which subsequently opened avenues for more complex development services.

The Evolving AI Agency Model

For years, the prevailing model for AI agencies revolved around developing custom AI solutions, automation, and software. While this remains a crucial component, the market is maturing, revealing a need for foundational AI understanding within organizations. Many companies struggle with AI adoption not due to a lack of technical expertise, but because of a deficit in organizational culture, processes, and data literacy.

Matteo’s journey exemplifies this shift. Initially focused on general AI development, he encountered significant resistance and a lack of understanding from clients. This led to a strategic pivot towards education and training, which proved to be a highly effective entry point and revenue generator.

Key Observations from the Italian Market

Matteo’s experience in the Italian market highlighted several critical points:

• Limited AI Understanding: Businesses often lacked a fundamental understanding of AI, its benefits, and its implications. This prevented them from appreciating the value of AI automation and software solutions.
• Missing Fundamentals: Companies were not technically unprepared but lacked essential foundational elements such as data culture, company culture, and standardized processes. These are prerequisites for successful AI integration.
• “Handbrake On” Adoption: The absence of these fundamentals meant AI adoption was slow and met with resistance. Clients were essentially “driving with the handbrake on,” hindering the effectiveness of AI implementations.
• Culture Over Technology: The primary barrier to AI adoption was not a technological limitation but a cultural one. Organizations needed a shift in mindset and approach before they could effectively leverage AI.

This realization fundamentally changed Matteo’s agency’s go-to-market strategy. Instead of leading with automation, the focus shifted to fostering understanding. Automation became a consequence of this newfound understanding, rather than the primary selling point.

The Internal Expert as a Catalyst

A significant epiphany for Matteo’s agency was the realization that creating internal AI experts within client companies dramatically accelerated AI adoption. When a company had even one strong internal champion, the path to successful AI integration became significantly smoother. This led to:

• Accelerated Adoption: Internal experts could champion AI initiatives, bridge communication gaps, and drive change.
• Easier Sales of Services: With a foundational understanding established, selling automation and other advanced AI services became more straightforward.
• Visible Momentum: Processes improved, teams adapted, and results became tangible, leading to increased client confidence and further investment.
• Informed Decision-Making: Companies that could track results were better positioned to make informed decisions, leading to more engagements with Matteo’s agency.

This model proved highly effective, with approximately 80% of companies that trained at least one internal AI expert ultimately becoming clients for broader AI services.

The “Foot-in-the-Door” Offer: AI Training and Education

Matteo’s agency, Morpheus, identified AI training and education as a powerful “foot-in-the-door” offer. This strategy served multiple purposes:

1. Market Penetration: It provided an accessible entry point for companies hesitant to commit to large-scale development projects.
2. Revenue Generation: The training programs themselves became a significant revenue stream, with workshops priced around $6,000 USD.
3. Client Cultivation: It allowed Morpheus to build trust, demonstrate expertise, and identify potential clients for downstream services.
4. Case Study Creation: By showcasing their own internal AI-driven marketing and operational optimizations, Morpheus acted as a living case study for the efficacy of AI.

The Offer Structure and Delivery

Morpheus offers two tiers of training:

• Basic Training: Delivered remotely, this tier focuses on introducing AI concepts, LLMs, knowledge bases, and prompting techniques. The goal is to provide a foundational understanding to a broader audience within the company.
• Advanced Training: This tier is priced higher and involves more in-depth instruction, often aimed at developing internal “champions” or experts. These can extend to 10-15 hours of work and are priced accordingly, potentially reaching $10,000 USD.

The delivery mechanism for these trainings has evolved. While initially conducted in person, Morpheus is actively productizing and scaling these offers for remote delivery via webinars. This allows for greater reach and efficiency.

The Core Value Proposition of the Training Offer

The training offer is not merely about explaining “how AI works.” It’s about training individuals on the methodologies Morpheus uses to optimize processes. This involves:

1. Initial Audit and Assessment: A crucial step is conducting an assessment to identify 2-3 real, repetitive, and easily optimizable processes within the client’s organization. This assessment can be semi-automated using AI tools that interview employees or analyze survey responses.
2. Process Optimization: Morpheus then optimizes these identified processes, demonstrating a significant ROI. These optimizations are often achievable with relatively simple AI tools and prompt engineering, taking only a few hours for Morpheus but yielding substantial time savings for the client.
3. Live Demos and Workshops: During workshops, Morpheus introduces key AI concepts (LLMs, prompting) and then presents the optimized version of the client’s own processes. This direct relevance breaks down resistance instantly. The power of live demonstrations, showcasing how a task can be completed significantly faster using AI, is paramount.
4. Competence Transfer: The training aims to transfer competence, not just provide entertainment. The focus is on teaching the logic behind AI optimization, enabling individuals to replicate these improvements.

Identifying AI Champions

A key outcome of the training is the identification and development of “AI Champions” within the client company. These are individuals who not only understand AI but can also begin to optimize their own processes and guide others. The training aims to create 2-3 such champions within a team of 50, fostering a bottom-up approach to AI adoption.

Post-Training Follow-up and Upselling

AI adoption is not a one-off event. Morpheus implements a four-week follow-up period, with one hour of engagement per week, to ensure true adoption and further identify AI champions. This follow-up phase is critical for:

• Ensuring Adoption: Providing ongoing support and guidance to integrate AI into daily workflows.
• Discovering Champions: Observing who is actively using AI and generating new ideas.
• Identifying Upsell Opportunities: This is where the value ladder truly comes into play. Champions often identify further complex needs and potential use cases that require custom development. This directly fuels the pipeline for Morpheus’s core development services.

The Value Ladder: From Training to Custom Development

The AI training and education offer serves as the initial step in a comprehensive value ladder. After establishing a foundational understanding and identifying internal champions, Morpheus can seamlessly transition to more advanced services.

The Role of Custom Development

While training is the entry point, custom AI development remains a core offering. The insights gained from training and the identification of AI champions directly inform these development projects.

• Champion-Driven Use Cases: AI champions, empowered by their training, often articulate specific needs and opportunities for custom development. This ensures that development efforts are aligned with real business requirements.
• Project Scale: Custom development projects can range from $20,000 to $80,000 USD or more, representing significant revenue opportunities.
• Long-Term Partnerships: By demonstrating value through training and identifying champions, Morpheus positions itself as a trusted, long-term partner. This leads to recurring revenue streams from ongoing projects and support.

Productizing Services for Scalability

A critical takeaway for any growing AI agency is the importance of productizing services. This means moving away from purely bespoke, time-intensive engagements towards offering standardized, scalable solutions.

• Scalable Training: As mentioned, Morpheus is actively productizing its training programs for remote delivery, enabling them to serve a larger client base without proportional increases in resources.
• AI Agents for Specific Tasks: Beyond training, Morpheus offers pre-built AI agents for common tasks like newsletter creation, LinkedIn post generation, and advertising. These are tangible products that can be sold independently or as part of a broader engagement.
• Recurrent Revenue: Productization and the development of long-term partnerships are key to establishing recurring revenue. Clients often engage Morpheus for ongoing projects, maintainance, and new development initiatives, creating a stable income stream.

Case Study: Morpheus’s Offer and Strategy

Morpheus targets businesses with annual revenues between $20 million and $150 million. This segment is large enough to have significant optimization potential but agile enough to adopt new technologies.

The Iterative Development of the Offer

Morpheus’s offer evolved through several stages:

• 2024: Started with AI system creation and AI automation.
• Discovery: Realized the importance of workshops and training.
• Current Offer:
  • AI System Creation: Custom automation and software development.
  • Workshops and Training:
    • Basic (Remote): Focus on foundational AI concepts, accessible to a broad audience.
    • Advanced (Higher Price Point): Focus on developing AI champions, offering deeper dives and customized solutions.
  • AI Agents: Pre-built tools for specific marketing and content creation tasks.

The Assessment and Optimization Process

The core of the training offer involves a structured approach to process assessment and optimization.

1. Automated Assessment:
   • Survey/Interview: Employees complete surveys or are interviewed (potentially by an AI agent) to identify repetitive and inefficient processes.
   • AI Analysis: Responses are analyzed by AI, with human oversight, to flag potential optimization opportunities.
2. Process Selection: Morpheus selects 2-3 key processes that are:
   • Repetitive: Performed frequently.
   • Easily Mappable: Clearly defined steps.
   • Quick to Optimize: Requiring minimal effort for significant impact.
   • Visibly Impactful: Demonstrating clear ROI for the client.
3. Optimization Demonstration:
   • Micro-Step Breakdown: The selected process is deconstructed into its fundamental steps.
   • Prompt Engineering and Tooling: Morpheus tests various prompts and AI tools (e.g., GPTs, specific LLMs) to establish an improved workflow. Effective prompt engineering is crucial here.
   • Live Demos: During workshops, these optimized processes are demonstrated live, showcasing how AI can perform the task significantly faster than manual methods. This is crucial for client engagement and buy-in.
4. Competence Transfer:
   • Step-by-Step Walkthrough: The exact steps taken to achieve the optimization are explained, from mapping and design to testing.
   • Focus on Logic: The emphasis is on understanding the underlying logic, enabling participants to apply similar methods to other processes.
   • Outcome: Participants gain the skills to create small automations, use GPTs, and understand AI principles, with the goal of developing internal AI champions.

The Follow-up and Upsell Mechanism

The post-training engagement is designed to solidify learning and generate further business.

• Duration: Four weeks of follow-up, one hour per week.
• Format: Group calls or structured check-ins.
• Objective:
  • Ensure AI adoption within the company.
  • Identify active users and potential AI champions.
  • Gather insights into emerging needs and complex use cases.
• Upsell Trigger: Discussions during the follow-up phase often reveal opportunities for custom development. Clients articulate further needs, which Morpheus then addresses with tailored quotations for their core development services. This is the direct path to larger projects, such as custom AI platforms or complex automation solutions. This aligns with the principles of building a profitable AI agency through strategic partnerships and service offerings.

Technical Considerations and Implementation Examples

While the transcript focuses on the business strategy, the underlying technical implementation of AI tools and prompt engineering is essential.

Prompt Engineering for Process Optimization

The core of demonstrating AI’s power in training lies in effective prompt engineering. For example, when optimizing an HR recruitment process:

Scenario: A recruitment team spends significant time manually researching potential candidates.

AI Tool: Perplexity or a custom GPT designed for candidate sourcing.

Prompt Strategy:

You are an AI assistant specialized in identifying top talent for [Industry/Role].
Given the following job description and company profile, identify 10 highly relevant candidates from publicly available professional networks.

Job Description:
[Paste Job Description Here]

Company Profile:
[Paste Company Profile Here]

For each candidate, provide:
1. Name
2. LinkedIn Profile URL (if available)
3. Key skills matching the job description
4. A brief summary of why they are a good fit, referencing specific experience.

Ensure the search is efficient and focuses on candidates with demonstrably relevant experience.

This type of prompt, when executed efficiently, can drastically reduce the time spent on manual research, illustrating a tangible benefit to the recruitment team.

Building Custom GPTs for Specific Tasks

The concept of creating custom GPTs for specific business functions is a key takeaway. For instance, a company might develop a GPT for:

• Sales Email Generation: Trained on successful past sales emails and product information.
• Customer Support Ticket Summarization: Capable of reading and summarizing complex support tickets.
• Internal Knowledge Base Querying: Allowing employees to ask natural language questions about company policies or procedures.

Example GPT Configuration (Conceptual):

• Name: Internal Policy Bot
• Description: Answers questions about company HR and IT policies.
• Instructions:
  • “You are an AI assistant designed to help employees find information quickly within our company’s internal knowledge base.
  • Access the provided document: company_policies_v3.pdf.
  • When a user asks a question, first try to find the answer directly within the document.
  • If the answer is not explicit, explain that you cannot find the specific information and suggest the user contact the relevant department (HR or IT).
  • Do not invent information.
  • Keep answers concise and to the point.”
• Knowledge Files: company_policies_v3.pdf

This demonstrates how readily available tools can be leveraged to create specialized AI solutions that address specific organizational needs. This is a core aspect of AI App Development & Marketing.

AI for Internal Operations and Marketing

Morpheus leverages AI not only for client services but also for its own operational efficiency and go-to-market strategy.

• LinkedIn Content Generation: Using AI to draft posts, identify trending topics, and optimize posting schedules to increase engagement and lead generation.
• Newsletter Launch: Employing AI to create content, identify target audiences, and manage distribution for a newsletter, demonstrating its utility for content marketing.
• Sales Process Automation: Building AI-driven automations within their CRM or sales platforms to streamline lead qualification, follow-up, and deal progression.

This internal application serves as a powerful demonstration of AI’s capabilities, acting as a real-world case study for potential clients.

Conclusion: The Future of AI Agencies

The AI agency space is moving beyond a singular focus on technical development. The success of Matteo’s approach underscores the immense value in providing foundational AI education and consulting. By acting as educators and facilitators of understanding, agencies can:

• Demystify AI: Make AI accessible and understandable for non-technical stakeholders.
• Build Trust: Establish credibility and long-term relationships with clients.
• Identify Needs: Uncover genuine business problems that AI can solve.
• Drive Adoption: Create internal champions who can evangelize AI within their organizations.
• Create Upsell Opportunities: Seamlessly transition clients to more complex and lucrative development projects.

For businesses looking to enter the AI agency space, especially those who are non-technical, focusing on education and consulting offers a robust and scalable path to success. The ability to demonstrate tangible results through optimized processes and the creation of internal AI champions provides a clear value proposition that leads to sustained growth and deeper client engagements.